Computation and prediction of linked access

ABSTRACT

An example operation includes one or more of detecting a fork in a supply-chain by a modeling node, resolving, by the modeling node, a branch prediction to determine a likely access control, generating, by the modeling node, a range of information based on a branch confidence level, and responsive to the resolution of the branch prediction, revoking access from a document or granting a greater access to the document based on the range.

BACKGROUND

A centralized database stores and maintains data in a single database(e.g., a database server) at one location. This location is often acentral computer, for example, a desktop central processing unit (CPU),a server CPU, or a mainframe computer. Information stored on acentralized database is typically accessible from multiple differentpoints. Multiple users or client workstations can work simultaneously onthe centralized database, for example, based on a client/serverconfiguration. A centralized database is easy to manage, maintain, andcontrol, especially for purposes of security because of its singlelocation. Within a centralized database, data redundancy is minimized asa single storing place of all data also implies that a given set of dataonly has one primary record.

SUMMARY

One example embodiment provides a system that includes a processor andmemory, wherein the processor is configured to perform one or more oftraverse a supply-chain downstream from an initial step, detect amulti-organization step, and responsive to the detection of themulti-organization step, execute a branch prediction algorithm todetermine downstream granted organizations.

Another example embodiment provides a system that includes a processorand memory, wherein the processor is configured to perform one or moreof detect a fork in a supply-chain, resolve a branch prediction todetermine a likely access control, generate a range of information basedon a branch confidence level, and responsive to the resolution of thebranch prediction, revoke access from a document or grant a greateraccess to the document based on the range.

Another example embodiment provides a method that includes one or moreof traversing, by a modeling node, a supply-chain downstream from aninitial step, detecting, by a modeling node, a multi-organization step,and responsive to the detection of the multi-organization step,executing a branch prediction algorithm to determine downstream grantedorganizations.

Another example embodiment provides a method that includes one or moreof detecting a fork in a supply-chain by a modeling node, resolving, bythe modeling node, a branch prediction to determine a likely accesscontrol, generating, by the modeling node, a range of information basedon a branch confidence level, and responsive to the resolution of thebranch prediction, revoking access from a document or granting a greateraccess to the document based on the range.

A further example embodiment provides a non-transitory computer readablemedium comprising instructions, that when read by a processor, cause theprocessor to perform one or more of traversing a supply-chain downstreamfrom an initial step, detecting a multi-organization step, andresponsive to the detection of the multi-organization step, executing abranch prediction algorithm to determine downstream grantedorganizations.

A further example embodiment provides a non-transitory computer readablemedium comprising instructions, that when read by a processor, cause theprocessor to perform one or more of detecting a fork in a supply-chain,resolving a branch prediction to determine a likely access control,generating a range of information based on a branch confidence level,and responsive to the resolution of the branch prediction, revokingaccess from a document or granting a greater access to the documentbased on the range.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A illustrates a network diagram of a system including a database,according to an example embodiment.

FIG. 1B illustrates a network diagram of a system including a database,according to another example embodiment.

FIG. 2A illustrates an example blockchain architecture configuration,according to example embodiments.

FIG. 2B illustrates a blockchain transactional flow, according toexample embodiments.

FIG. 3A illustrates a permissioned network, according to exampleembodiments.

FIG. 3B illustrates another permissioned network, according to exampleembodiments.

FIG. 3C illustrates a permissionless network, according to exampleembodiments.

FIG. 4A illustrates a flow diagram, according to example embodiments.

FIG. 4B illustrates a further flow diagram, according to exampleembodiments.

FIG. 4C illustrates a flow diagram, according to example embodiments.

FIG. 4D illustrates a further flow diagram, according to exampleembodiments.

FIG. 5A illustrates an example system configured to perform one or moreoperations described herein, according to example embodiments.

FIG. 5B illustrates another example system configured to perform one ormore operations described herein, according to example embodiments.

FIG. 5C illustrates a further example system configured to utilize asmart contract, according to example embodiments.

FIG. 5D illustrates yet another example system configured to utilize ablockchain, according to example embodiments.

FIG. 6A illustrates a process for a new block being added to adistributed ledger, according to example embodiments.

FIG. 6B illustrates contents of a new data block, according to exampleembodiments.

FIG. 6C illustrates a blockchain for digital content, according toexample embodiments.

FIG. 6D illustrates a block which may represent the structure of blocksin the blockchain, according to example embodiments.

FIG. 7A illustrates an example blockchain which stores machine learning(artificial intelligence) data, according to example embodiments.

FIG. 7B illustrates an example quantum-secure blockchain, according toexample embodiments.

FIG. 8 illustrates an example system that supports one or more of theexample embodiments.

DETAILED DESCRIPTION

It will be readily understood that the instant components, as generallydescribed and illustrated in the figures herein, may be arranged anddesigned in a wide variety of different configurations. Thus, thefollowing detailed description of the embodiments of at least one of amethod, apparatus, non-transitory computer readable medium and system,as represented in the attached figures, is not intended to limit thescope of the application as claimed but is merely representative ofselected embodiments.

The instant features, structures, or characteristics as describedthroughout this specification may be combined or removed in any suitablemanner in one or more embodiments. For example, the usage of the phrases“example embodiments”, “some embodiments”, or other similar language,throughout this specification refers to the fact that a particularfeature, structure, or characteristic described in connection with theembodiment may be included in at least one embodiment. Thus, appearancesof the phrases “example embodiments”, “in some embodiments”, “in otherembodiments”, or other similar language, throughout this specificationdo not necessarily all refer to the same group of embodiments, and thedescribed features, structures, or characteristics may be combined orremoved in any suitable manner in one or more embodiments. Further, inthe diagrams, any connection between elements can permit one-way and/ortwo-way communication even if the depicted connection is a one-way ortwo-way arrow. Also, any device depicted in the drawings can be adifferent device. For example, if a mobile device is shown sendinginformation, a wired device could also be used to send the information.

In addition, while the term “message” may have been used in thedescription of embodiments, the application may be applied to many typesof networks and data. Furthermore, while certain types of connections,messages, and signaling may be depicted in exemplary embodiments, theapplication is not limited to a certain type of connection, message, andsignaling.

Example embodiments provide methods, systems, components, non-transitorycomputer readable media, devices, and/or networks, which provide forcomputation, verification and prediction of a linked access inblockchain networks.

In one embodiment the application utilizes a decentralized database(such as a blockchain) that is a distributed storage system, whichincludes multiple nodes that communicate with each other. Thedecentralized database includes an append-only immutable data structureresembling a distributed ledger capable of maintaining records betweenmutually untrusted parties. The untrusted parties are referred to hereinas peers or peer nodes. Each peer maintains a copy of the databaserecords and no single peer can modify the database records without aconsensus being reached among the distributed peers. For example, thepeers may execute a consensus protocol to validate blockchain storagetransactions, group the storage transactions into blocks, and build ahash chain over the blocks. This process forms the ledger by orderingthe storage transactions, as is necessary, for consistency. In variousembodiments, a permissioned and/or a permissionless blockchain can beused. In a public or permission-less blockchain, anyone can participatewithout a specific identity. Public blockchains can involve nativecryptocurrency and use consensus based on various protocols such asProof of Work (PoW). On the other hand, a permissioned blockchaindatabase provides secure interactions among a group of entities whichshare a common goal but which do not fully trust one another, such asbusinesses that exchange funds, goods, information, and the like.

This application can utilize a blockchain that operates arbitrary,programmable logic, tailored to a decentralized storage scheme andreferred to as “smart contracts” or “chaincodes.” In some cases,specialized chaincodes may exist for management functions and parameterswhich are referred to as system chaincode. The application can furtherutilize smart contracts that are trusted distributed applications whichleverage tamper-proof properties of the blockchain database and anunderlying agreement between nodes, which is referred to as anendorsement or endorsement policy. Blockchain transactions associatedwith this application can be “endorsed” before being committed to theblockchain while transactions, which are not endorsed, are disregarded.An endorsement policy allows chaincode to specify endorsers for atransaction in the form of a set of peer nodes that are necessary forendorsement. When a client sends the transaction to the peers specifiedin the endorsement policy, the transaction is executed to validate thetransaction. After validation, the transactions enter an ordering phasein which a consensus protocol is used to produce an ordered sequence ofendorsed transactions grouped into blocks.

This application can utilize nodes that are the communication entitiesof the blockchain system. A “node” may perform a logical function in thesense that multiple nodes of different types can run on the samephysical server. Nodes are grouped in trust domains and are associatedwith logical entities that control them in various ways. Nodes mayinclude different types, such as a client or submitting-client nodewhich submits a transaction-invocation to an endorser (e.g., peer), andbroadcasts transaction-proposals to an ordering service (e.g., orderingnode). Another type of node is a peer node which can receive clientsubmitted transactions, commit the transactions and maintain a state anda copy of the ledger of blockchain transactions. Peers can also have therole of an endorser, although it is not a requirement. Anordering-service-node or orderer is a node running the communicationservice for all nodes, and which implements a delivery guarantee, suchas a broadcast to each of the peer nodes in the system when committingtransactions and modifying a world state of the blockchain, which isanother name for the initial blockchain transaction which normallyincludes control and setup information.

This application can utilize a ledger that is a sequenced,tamper-resistant record of all state transitions of a blockchain. Statetransitions may result from chaincode invocations (i.e., transactions)submitted by participating parties (e.g., client nodes, ordering nodes,endorser nodes, peer nodes, etc.). Each participating party (such as apeer node) can maintain a copy of the ledger. A transaction may resultin a set of asset key-value pairs being committed to the ledger as oneor more operands, such as creates, updates, deletes, and the like. Theledger includes a blockchain (also referred to as a chain) which is usedto store an immutable, sequenced record in blocks. The ledger alsoincludes a state database which maintains a current state of theblockchain.

This application can utilize a chain that is a transaction log which isstructured as hash-linked blocks, and each block contains a sequence ofN transactions where N is equal to or greater than one. The block headerincludes a hash of the block's transactions, as well as a hash of theprior block's header. In this way, all transactions on the ledger may besequenced and cryptographically linked together. Accordingly, it is notpossible to tamper with the ledger data without breaking the hash links.A hash of a most recently added blockchain block represents everytransaction on the chain that has come before it, making it possible toensure that all peer nodes are in a consistent and trusted state. Thechain may be stored on a peer node file system (i.e., local, attachedstorage, cloud, etc.), efficiently supporting the append-only nature ofthe blockchain workload.

The current state of the immutable ledger represents the latest valuesfor all keys that are included in the chain transaction log. Since thecurrent state represents the latest key values known to a channel, it issometimes referred to as a world state. Chaincode invocations executetransactions against the current state data of the ledger. To make thesechaincode interactions efficient, the latest values of the keys may bestored in a state database. The state database may be simply an indexedview into the chain's transaction log, it can therefore be regeneratedfrom the chain at any time. The state database may automatically berecovered (or generated if needed) upon peer node startup, and beforetransactions are accepted.

Some benefits of the instant solutions described and depicted hereininclude a method and system for computation, verification and predictionof a linked access in blockchain networks. The exemplary embodimentssolve the issues of time and trust by extending features of a databasesuch as immutability, digital signatures and being a single source oftruth. The exemplary embodiments provide a solution for computation,verification and prediction of a linked access in blockchain-basednetwork. The blockchain networks may be homogenous based on the assettype and rules that govern the assets based on the smart contracts.

Blockchain is different from a traditional database in that blockchainis not a central storage, but rather a decentralized, immutable, andsecure storage, where nodes must share in changes to records in thestorage. Some properties that are inherent in blockchain and which helpimplement the blockchain include, but are not limited to, an immutableledger, smart contracts, security, privacy, decentralization, consensus,endorsement, accessibility, and the like, which are further describedherein. According to various aspects, the system for computation,verification and prediction of a linked access in blockchain networks isimplemented due to immutable accountability, security, privacy,permitted decentralization, availability of smart contracts,endorsements and accessibility that are inherent and unique toblockchain. In particular, the blockchain ledger data is immutable andthat provides for efficient method for computation, verification andprediction of a linked access in blockchain networks. Also, use of theencryption in the blockchain provides security and builds trust. Thesmart contract manages the state of the asset to complete thelife-cycle. The example blockchains are permission decentralized. Thus,each end user may have its own ledger copy to access. Multipleorganizations (and peers) may be on-boarded on the blockchain network.The key organizations may serve as endorsing peers to validate the smartcontract execution results, read-set and write-set. In other words, theblockchain inherent features provide for efficient implementation of amethod for computation, verification and prediction of a linked accessin blockchain networks.

One of the benefits of the example embodiments is that it improves thefunctionality of a computing system by implementing a method forcomputation, verification and prediction of a linked access inblockchain-based systems. Through the blockchain system describedherein, a computing system can perform functionality for computation,verification and prediction of a linked access in blockchain networks byproviding access to capabilities such as distributed ledger, peers,encryption technologies, MSP, event handling, etc. Also, the blockchainenables to create a business network and make any users or organizationsto on-board for participation. As such, the blockchain is not just adatabase. The blockchain comes with capabilities to create a BusinessNetwork of users and on-board/off-board organizations to collaborate andexecute service processes in the form of smart contracts.

The example embodiments provide numerous benefits over a traditionaldatabase. For example, through the blockchain the embodiments providefor immutable accountability, security, privacy, permitteddecentralization, availability of smart contracts, endorsements andaccessibility that are inherent and unique to the blockchain.

Meanwhile, a traditional database could not be used to implement theexample embodiments because it does not bring all parties on thebusiness network, it does not create trusted collaboration and does notprovide for an efficient storage of digital assets. The traditionaldatabase does not provide for a tamper proof storage and does notprovide for preservation of the digital assets being stored. Thus, theproposed method for computation, verification and prediction of a linkedaccess in blockchain networks cannot be implemented in the traditionaldatabase.

Meanwhile, if a traditional database were to be used to implement theexample embodiments, the example embodiments would have suffered fromunnecessary drawbacks such as search capability, lack of security andslow speed of transactions. Additionally, the automated method forcomputation, verification and prediction of a linked access inblockchain networks would simply not be possible.

A centralized database has a single point of failure. In particular, ifa failure occurs (for example, a hardware, firmware, and/or a softwarefailure), all data within the database is lost and work of all users isinterrupted. In addition, centralized databases are highly dependent onnetwork connectivity. As a result, the slower the connection, the amountof time needed for each database access is increased. Occurrence ofbottlenecks is possible when a centralized database experiences hightraffic due to a single location. Furthermore, a centralized databaseprovides limited access to data because only one copy of the data ismaintained by the database. As a result, multiple devices cannot accessthe same piece of data at the same time without creating significantproblems or risk overwriting stored data. Furthermore, because adatabase storage system has minimal to no data redundancy, data that isunexpectedly lost is very difficult to retrieve other than throughmanual operation from back-up storage. Thus, a use of blockchains fordata storage may be more efficient that with a database.

Supply-chains are often based on an underlying blockchain. There existsa need to control sharing of data across members of a supply-chain on adynamic subset of data. Current technology utilizes implicit lot levelinformation on linked supply-chain data to allow resolution of accesscontrol. However, it is likely that organizations involved in thesupply-chain may provide information to determine a cross organizationproduct level supply-chain model. When data is shared betweenorganizations, there is a potential to infer a product levelsupply-chain implicitly from the data. The product level supply-chainmodel can lead to insights about access control that can providevaluable optimizations, predictions and validation measures. However, amethod for determining a centralized secure supply-chain model acrossdifferent organizations is not available.

Accordingly, the example embodiments provide one or more solutions forverification and prediction of a linked access in the blockchainnetworks.

The example embodiments also change how data may be stored within ablock structure of the blockchain. For example, a digital asset data maybe securely stored within a certain portion of the data block (i.e.,within header, data segment, or metadata). By storing the digital assetdata within data blocks of a blockchain, the digital asset data may beappended to an immutable blockchain ledger through a hash-linked chainof blocks. In some embodiments, the data block may be different than atraditional data block by having a personal data associated with thedigital asset not stored together with the assets within a traditionalblock structure of a blockchain. By removing the personal dataassociated with the digital asset, the blockchain can provide thebenefit of anonymity based on immutable accountability and security.

According to the exemplary embodiments, a method and system forcomputation, verification and prediction of a linked access inblockchain networks are provided. In one embodiment, determination ofproduct level multi-party supply-chain model may be based on one of thefollowing:

-   -   An agreed upon smart contract;    -   Inferences from document metadata;    -   Utilization of the inherent nature of and insights found in        modeled supply-chain to enact optimizations in data entitlement        computation;    -   Prospective data sharing using a supply-chain model and branch        prediction techniques to reason about the future; and    -   Validation of incoming documents based on a learned or explicit        product level multi-party supply chain model and learned or        explicit cues.

According to one exemplary embodiment, smart contracts may be used formodeling of a supply-chain. A smart contract may contain an agreed uponset of conditions that all parties in a step must agree upon and asupply-chain model for a given product. Once verified between allparties, a subset of potential entitled organizations may be easilydetermined. Validation on documents that fall in or out of thissupply-chain becomes much easier. As the actual supply-chain changes,updates to the supply-chain model may require additional submissions tothe above smart contract containing the agreed upon updates.

In one exemplary embodiment, learning of the supply-chain from documentinformation may be used. The model may use document metadata to build upand add to a learned internal supply-chain structure. Once a certainaspect from the metadata detailing a piece of the supply-chain appearsenough times, it may be added to the internal supply-chain structure.Note that the system, advantageously, does not need explicitsupply-chain information from participants. A disadvantage is that anynew information (correct or not) may be considered “new” supply-chaininformation. Knowing when to keep or when to discard information in themetadata requires repetition and may always be used as a layer ofvalidation brought to the user. Both of the above methods may result inthe same advantages and optimizations once a model is determined.

All master data entitlement may be resolved at the determination of asupply-chain, where all master data should be entitled to allorganizations downstream. No document will need to update master data,as on ingestion of master data, entitlement is fully computed meaningthat only instance level documents (e.g., events, transactions, etc.)will need to update other instance level documents.

In one exemplary embodiment, instance level optimizations may beimplemented. When there are multiple organizations at one step, themaster data level supply-chain may not have enough information, as itmay not be able to reason about lot level events that go to differentorganizations. When a supply-chain is linear (each step in the supplychain only contains one organization), entitlement is fully solved, asthe instance level entitlement is completely represented by the masterdata level supply-chain.

For example, a given supply chain which has a multi-organization step atsome step S, may be used to determine:

-   -   Downstream organizations that are granted access: traverse the        supply chain downstream from S until a multi-organization step        is reached. At that point, follow the branch prediction        algorithm to determine downstream granted organizations.    -   Upstream documents that need to be updated: traverse the master        data level graph upstream from S until a multi-organization step        is reached. Up until that point, no documents need to be        updated, as they will have followed the downstream graph and        gotten correct grants. After that point, follow the branch        prediction algorithm. This approach leads to the smallest number        of document updates and traversals by taking advantage of the        linear nature of subsections of all supply-chains.

According to one exemplary embodiment, branch prediction and shared dataresolution may be implemented. In the event a supply-chain comes to afork, branch prediction techniques to best determine the most likelyaccess control may be used. Note that the fork may be a spot (i.e., anode of the graph) from where access may be granted in the directions ofdifferent branches based on branch confidence. Given varying levels ofbranch confidence, a range of (e.g., low-risk to high-risk) informationmay be revealed. A low confidence in a branch would result in low riskinformation being granted. Lower risk information may include: productIDs, locations involved, master data level information, etc. Highconfidence in a branch would result in potentially riskier informationbeing granted. Higher risk information may include: quantities,temperatures, transactional information, instance level information,etc. What is determined to be lower or higher risk information isdependent on the supply-chain and involved partners. An input from theinvolved organizations may be taken to better define the risk level ofcertain types of information. Once the branch prediction is resolved,standard branch prediction procedures may be followed to revoke andgrant greater access to the document. If the branch followed isdetermined to be incorrect, a document may be fully revoked and only lowrisk information is given to an incorrect party. If the branch followedis determined to be correct, the full document may be revealed.

According to one exemplary embodiment, incoming data may be validatedbased on cues and supply-chain model. The supply-chain data oftencontains metadata information, or “cues,” about goods flowing through asupply chain such as: temperature, geo-location, origination point,expiration date, GTIN (private label vs non-private label), whether ornot a good is refrigerated. Criteria exist for many of these cues whichmay allow the exemplary system to bypass the standard access controlalgorithm. Submitted data that is incongruent with supply-chain modelwill be considered invalid. These criteria may be thresholds on anumerical range (e.g., a temperature is too warm or too cold) or Booleanvalues (e.g., whether or not the GTIN reflects private label goods). Themechanism used to bypass standard access control application may be oneof the following:

-   -   The data is invalid given a system of learned cues (incorrect        data submitted by a user);    -   The data can be explicitly entitled (e.g., private label goods);    -   In a learned supply chain, cues are used to reduce the number of        organizations in a sub-graph to one, leading to optimizations        outlined above;    -   These thresholds can either be learned by a system over time or        set explicitly by an organization submitting the data.

For example, if frozen beef shipped by a supplier A is usually around 32degrees Fahrenheit and the system receives data that recorded beefstored at 3200 degrees, the system may alert the client that they mayhave submitted invalid data. If the client confirms the invalid data,the system does not need to entitle the data to other organizations.Threshold can be set by the organization—e.g., an organization says toconsider data invalid if it passes through a location that they do notown. If submitted data is considered likely invalid, the system canvalidate the data by prompting input from submitting organization. Thismeans that incorrect data will not impact the access control model andresult in oversharing of data. This also means that insights derivedfrom the supply-chain data will be more likely to be accurate due tominimized invalid data in the system.

FIG. 1A illustrates a logic network diagram for computation,verification and prediction of a linked access in a blockchain network,according to example embodiments.

Referring to FIG. 1A, the example network 100 includes a modeling node102 connected to a blockchain 106 that has a ledger 108 for storingsupply-chain data 110. While this example describes in detail only onemodeling node 102, multiple such nodes may be connected to theblockchain 106. It should be understood that the modeling node 102 mayinclude additional components and that some of the components describedherein may be removed and/or modified without departing from a scope ofthe modeling node 102 disclosed herein. The modeling node 102 may be acomputing device or a server computer, or the like, and may include aprocessor 104, which may be a semiconductor-based microprocessor, acentral processing unit (CPU), an application specific integratedcircuit (ASIC), a field-programmable gate array (FPGA), and/or anotherhardware device. Although a single processor 104 is depicted, it shouldbe understood that the modeling node 102 may include multipleprocessors, multiple cores, or the like, without departing from thescope of the modeling node 102 system.

The modeling node 102 may also include a non-transitory computerreadable medium 112 that may have stored thereon machine-readableinstructions executable by the processor 104. Examples of themachine-readable instructions are shown as 114-118 and are furtherdiscussed below. Examples of the non-transitory computer readable medium112 may include an electronic, magnetic, optical, or other physicalstorage device that contains or stores executable instructions. Forexample, the non-transitory computer readable medium 112 may be a RandomAccess memory (RAM), an Electrically Erasable Programmable Read-OnlyMemory (EEPROM), a hard disk, an optical disc, or other type of storagedevice.

The processor 104 may execute the machine-readable instructions 114 totraverse a supply-chain downstream from an initial step. As discussedabove, the blockchain ledger 108 may store the supply-chain data. Theblockchain 106 network may be configured to use one or more smartcontracts that manage transactions for multiple participating nodes.

The processor 104 may execute the machine-readable instructions 116 todetect a multi-organization step. The processor 104 may execute themachine-readable instructions 118 to, responsive to the detection of themulti-organization step, execute a branch prediction algorithm todetermine downstream granted organizations.

FIG. 1B illustrates a logic network diagram for computation,verification and prediction of a linked access in blockchain networks,according to example embodiments.

Referring to FIG. 1B, the example network 130 includes a modeling node102 connected to a blockchain 106 that has a ledger 108 for storingsupply-chain data 110. While this example describes in detail only onemodeling node 102, multiple such nodes may be connected to theblockchain 106. It should be understood that the modeling node 102 mayinclude additional components and that some of the components describedherein may be removed and/or modified without departing from a scope ofthe modeling node 102 disclosed herein. The modeling node 102 may be acomputing device or a server computer, or the like, and may include aprocessor 104, which may be a semiconductor-based microprocessor, acentral processing unit (CPU), an application specific integratedcircuit (ASIC), a field-programmable gate array (FPGA), and/or anotherhardware device. Although a single processor 104 is depicted, it shouldbe understood that the modeling node 102 may include multipleprocessors, multiple cores, or the like, without departing from thescope of the modeling node 102 system.

The modeling node 102 may also include a non-transitory computerreadable medium 112′ that may have stored thereon machine-readableinstructions executable by the processor 104. Examples of themachine-readable instructions are shown as 113-119 and are furtherdiscussed below. Examples of the non-transitory computer readable medium112′ may include an electronic, magnetic, optical, or other physicalstorage device that contains or stores executable instructions. Forexample, the non-transitory computer readable medium 112′ may be aRandom Access memory (RAM), an Electrically Erasable ProgrammableRead-Only Memory (EEPROM), a hard disk, an optical disc, or other typeof storage device.

The processor 104 may execute the machine-readable instructions 113 todetect a fork in a supply-chain. The blockchain 106 network may beconfigured to use one or more smart contracts that manage transactionsfor multiple participating nodes. The processor 104 may execute themachine-readable instructions 115 to resolve a branch prediction todetermine a likely access control. The processor 104 may execute themachine-readable instructions 117 to generate a range of informationbased on a branch confidence level. The processor 104 may execute themachine-readable instructions 119 to, responsive to the resolution ofthe branch prediction, revoke access from a document or grant a greateraccess to the document based on the range.

FIG. 2A illustrates a blockchain architecture configuration 200,according to example embodiments. Referring to FIG. 2A, the blockchainarchitecture 200 may include certain blockchain elements, for example, agroup of blockchain nodes 202. The blockchain nodes 202 may include oneor more nodes 204-210 (these four nodes are depicted by example only).These nodes participate in a number of activities, such as blockchaintransaction addition and validation process (consensus). One or more ofthe blockchain nodes 204-210 may endorse transactions based onendorsement policy and may provide an ordering service for allblockchain nodes in the architecture 200. A blockchain node may initiatea blockchain authentication and seek to write to a blockchain immutableledger stored in blockchain layer 216, a copy of which may also bestored on the underpinning physical infrastructure 214. The blockchainconfiguration may include one or more applications 224 which are linkedto application programming interfaces (APIs) 222 to access and executestored program/application code 220 (e.g., chaincode, smart contracts,etc.) which can be created according to a customized configurationsought by participants and can maintain their own state, control theirown assets, and receive external information. This can be deployed as atransaction and installed, via appending to the distributed ledger, onall blockchain nodes 204-210.

The blockchain base or platform 212 may include various layers ofblockchain data, services (e.g., cryptographic trust services, virtualexecution environment, etc.), and underpinning physical computerinfrastructure that may be used to receive and store new transactionsand provide access to auditors which are seeking to access data entries.The blockchain layer 216 may expose an interface that provides access tothe virtual execution environment necessary to process the program codeand engage the physical infrastructure 214. Cryptographic trust services218 may be used to verify transactions such as asset exchangetransactions and keep information private.

The blockchain architecture configuration of FIG. 2A may process andexecute program/application code 220 via one or more interfaces exposed,and services provided, by blockchain platform 212. The code 220 maycontrol blockchain assets. For example, the code 220 can store andtransfer data, and may be executed by nodes 204-210 in the form of asmart contract and associated chaincode with conditions or other codeelements subject to its execution. As a non-limiting example, smartcontracts may be created to execute reminders, updates, and/or othernotifications subject to the changes, updates, etc. The smart contractscan themselves be used to identify rules associated with authorizationand access requirements and usage of the ledger. For example, thesupply-chain downstream information 226 may be processed by one or moreprocessing entities (e.g., virtual machines) included in the blockchainlayer 216. The result 228 may include determined downstream grantedorganizations. The physical infrastructure 214 may be utilized toretrieve any of the data or information described herein.

A smart contract may be created via a high-level application andprogramming language, and then written to a block in the blockchain. Thesmart contract may include executable code which is registered, stored,and/or replicated with a blockchain (e.g., distributed network ofblockchain peers). A transaction is an execution of the smart contractcode which can be performed in response to conditions associated withthe smart contract being satisfied. The executing of the smart contractmay trigger a trusted modification(s) to a state of a digital blockchainledger. The modification(s) to the blockchain ledger caused by the smartcontract execution may be automatically replicated throughout thedistributed network of blockchain peers through one or more consensusprotocols.

The smart contract may write data to the blockchain in the format ofkey-value pairs. Furthermore, the smart contract code can read thevalues stored in a blockchain and use them in application operations.The smart contract code can write the output of various logic operationsinto the blockchain. The code may be used to create a temporary datastructure in a virtual machine or other computing platform. Data writtento the blockchain can be public and/or can be encrypted and maintainedas private. The temporary data that is used/generated by the smartcontract is held in memory by the supplied execution environment, thendeleted once the data needed for the blockchain is identified.

A chaincode may include the code interpretation of a smart contract,with additional features. As described herein, the chaincode may beprogram code deployed on a computing network, where it is executed andvalidated by chain validators together during a consensus process. Thechaincode receives a hash and retrieves from the blockchain a hashassociated with the data template created by use of a previously storedfeature extractor. If the hashes of the hash identifier and the hashcreated from the stored identifier template data match, then thechaincode sends an authorization key to the requested service. Thechaincode may write to the blockchain data associated with thecryptographic details.

FIG. 2B illustrates an example of a blockchain transactional flow 250between nodes of the blockchain in accordance with an exampleembodiment. Referring to FIG. 2B, the transaction flow may include atransaction proposal 291 sent by an application client node 260 to anendorsing peer node 281. The endorsing peer 281 may verify the clientsignature and execute a chaincode function to initiate the transaction.The output may include the chaincode results, a set of key/valueversions that were read in the chaincode (read set), and the set ofkeys/values that were written in chaincode (write set). The proposalresponse 292 is sent back to the client 260 along with an endorsementsignature, if approved. The client 260 assembles the endorsements into atransaction payload 293 and broadcasts it to an ordering service node284. The ordering service node 284 then delivers ordered transactions asblocks to all peers 281-283 on a channel. Before committal to theblockchain, each peer 281-283 may validate the transaction. For example,the peers may check the endorsement policy to ensure that the correctallotment of the specified peers have signed the results andauthenticated the signatures against the transaction payload 293.

Referring again to FIG. 2B, the client node 260 initiates thetransaction 291 by constructing and sending a request to the peer node281, which is an endorser. The client 260 may include an applicationleveraging a supported software development kit (SDK), which utilizes anavailable API to generate a transaction proposal. The proposal is arequest to invoke a chaincode function so that data can be read and/orwritten to the ledger (i.e., write new key value pairs for the assets).The SDK may serve as a shim to package the transaction proposal into aproperly architected format (e.g., protocol buffer over a remoteprocedure call (RPC)) and take the client's cryptographic credentials toproduce a unique signature for the transaction proposal.

In response, the endorsing peer node 281 may verify (a) that thetransaction proposal is well formed, (b) the transaction has not beensubmitted already in the past (replay-attack protection), (c) thesignature is valid, and (d) that the submitter (client 260, in theexample) is properly authorized to perform the proposed operation onthat channel. The endorsing peer node 281 may take the transactionproposal inputs as arguments to the invoked chaincode function. Thechaincode is then executed against a current state database to producetransaction results including a response value, read set, and write set.However, no updates are made to the ledger at this point. In 292, theset of values, along with the endorsing peer node's 281 signature ispassed back as a proposal response 292 to the SDK of the client 260which parses the payload for the application to consume.

In response, the application of the client 260 inspects/verifies theendorsing peers signatures and compares the proposal responses todetermine if the proposal response is the same. If the chaincode onlyqueried the ledger, the application would inspect the query response andwould typically not submit the transaction to the ordering node service284. If the client application intends to submit the transaction to theordering node service 284 to update the ledger, the applicationdetermines if the specified endorsement policy has been fulfilled beforesubmitting (i.e., did all peer nodes necessary for the transactionendorse the transaction). Here, the client may include only one ofmultiple parties to the transaction. In this case, each client may havetheir own endorsing node, and each endorsing node will need to endorsethe transaction. The architecture is such that even if an applicationselects not to inspect responses or otherwise forwards an unendorsedtransaction, the endorsement policy will still be enforced by peers andupheld at the commit validation phase.

After successful inspection, in step 293 the client 260 assemblesendorsements into a transaction and broadcasts the transaction proposaland response within a transaction message to the ordering node 284. Thetransaction may contain the read/write sets, the endorsing peerssignatures and a channel ID. The ordering node 284 does not need toinspect the entire content of a transaction in order to perform itsoperation, instead the ordering node 284 may simply receive transactionsfrom all channels in the network, order them chronologically by channel,and create blocks of transactions per channel.

The blocks of the transaction are delivered from the ordering node 284to all peer nodes 281-283 on the channel. The transactions 294 withinthe block are validated to ensure any endorsement policy is fulfilledand to ensure that there have been no changes to ledger state for readset variables since the read set was generated by the transactionexecution. Transactions in the block are tagged as being valid orinvalid. Furthermore, in step 295 each peer node 281-283 appends theblock to the channel's chain, and for each valid transaction the writesets are committed to current state database. An event is emitted, tonotify the client application that the transaction (invocation) has beenimmutably appended to the chain, as well as to notify whether thetransaction was validated or invalidated.

FIG. 3A illustrates an example of a permissioned blockchain network 300,which features a distributed, decentralized peer-to-peer architecture.In this example, a blockchain user 302 may initiate a transaction to thepermissioned blockchain 304. In this example, the transaction can be adeploy, invoke, or query, and may be issued through a client-sideapplication leveraging an SDK, directly through an API, etc. Networksmay provide access to a regulator 306, such as an auditor. A blockchainnetwork operator 308 manages member permissions, such as enrolling theregulator 306 as an “auditor” and the blockchain user 302 as a “client”.An auditor could be restricted only to querying the ledger whereas aclient could be authorized to deploy, invoke, and query certain types ofchaincode.

A blockchain developer 310 can write chaincode and client-sideapplications. The blockchain developer 310 can deploy chaincode directlyto the network through an interface. To include credentials from atraditional data source 312 in chaincode, the developer 310 could use anout-of-band connection to access the data. In this example, theblockchain user 302 connects to the permissioned blockchain 304 througha peer node 314. Before proceeding with any transactions, the peer node314 retrieves the user's enrollment and transaction certificates from acertificate authority 316, which manages user roles and permissions. Insome cases, blockchain users must possess these digital certificates inorder to transact on the permissioned blockchain 304. Meanwhile, a userattempting to utilize chaincode may be required to verify theircredentials on the traditional data source 312. To confirm the user'sauthorization, chaincode can use an out-of-band connection to this datathrough a traditional processing platform 318.

FIG. 3B illustrates another example of a permissioned blockchain network320, which features a distributed, decentralized peer-to-peerarchitecture. In this example, a blockchain user 322 may submit atransaction to the permissioned blockchain 324. In this example, thetransaction can be a deploy, invoke, or query, and may be issued througha client-side application leveraging an SDK, directly through an API,etc. Networks may provide access to a regulator 326, such as an auditor.A blockchain network operator 328 manages member permissions, such asenrolling the regulator 326 as an “auditor” and the blockchain user 322as a “client.” An auditor could be restricted only to querying theledger whereas a client could be authorized to deploy, invoke, and querycertain types of chaincode.

A blockchain developer 330 writes chaincode and client-sideapplications. The blockchain developer 330 can deploy chaincode directlyto the network through an interface. To include credentials from atraditional data source 332 in chaincode, the developer 330 could use anout-of-band connection to access the data. In this example, theblockchain user 322 connects to the network through a peer node 334.Before proceeding with any transactions, the peer node 334 retrieves theuser's enrollment and transaction certificates from the certificateauthority 336. In some cases, blockchain users must possess thesedigital certificates in order to transact on the permissioned blockchain324. Meanwhile, a user attempting to utilize chaincode may be requiredto verify their credentials on the traditional data source 332. Toconfirm the user's authorization, chaincode can use an out-of-bandconnection to this data through a traditional processing platform 338.

In some embodiments, the blockchain herein may be a permissionlessblockchain. In contrast with permissioned blockchains which requirepermission to join, anyone can join a permissionless blockchain. Forexample, to join a permissionless blockchain a user may create apersonal address and begin interacting with the network, by submittingtransactions, and hence adding entries to the ledger. Additionally, allparties have the choice of running a node on the system and employingthe mining protocols to help verify transactions.

FIG. 3C illustrates a process 350 of a transaction being processed by apermissionless blockchain 352 including a plurality of nodes 354. Asender 356 desires to send payment or some other form of value (e.g., adeed, medical records, a contract, a good, a service, or any other assetthat can be encapsulated in a digital record) to a recipient 358 via thepermissionless blockchain 352. In one embodiment, each of the senderdevice 356 and the recipient device 358 may have digital wallets(associated with the blockchain 352) that provide user interfacecontrols and a display of transaction parameters. In response, thetransaction is broadcast throughout the blockchain 352 to the nodes 354.Depending on the blockchain's 352 network parameters the nodes verify360 the transaction based on rules (which may be pre-defined ordynamically allocated) established by the permissionless blockchain 352creators. For example, this may include verifying identities of theparties involved, etc. The transaction may be verified immediately or itmay be placed in a queue with other transactions and the nodes 354determine if the transactions are valid based on a set of network rules.

In structure 362, valid transactions are formed into a block and sealedwith a lock (hash). This process may be performed by mining nodes amongthe nodes 354. Mining nodes may utilize additional software specificallyfor mining and creating blocks for the permissionless blockchain 352.Each block may be identified by a hash (e.g., 256 bit number, etc.)created using an algorithm agreed upon by the network. Each block mayinclude a header, a pointer or reference to a hash of a previous block'sheader in the chain, and a group of valid transactions. The reference tothe previous block's hash is associated with the creation of the secureindependent chain of blocks.

Before blocks can be added to the blockchain, the blocks must bevalidated. Validation for the permissionless blockchain 352 may includea proof-of-work (PoW) which is a solution to a puzzle derived from theblock's header. Although not shown in the example of FIG. 3C, anotherprocess for validating a block is proof-of-stake. Unlike theproof-of-work, where the algorithm rewards miners who solve mathematicalproblems, with the proof of stake, a creator of a new block is chosen ina deterministic way, depending on its wealth, also defined as “stake.”Then, a similar proof is performed by the selected/chosen node.

With mining 364, nodes try to solve the block by making incrementalchanges to one variable until the solution satisfies a network-widetarget. This creates the PoW thereby ensuring correct answers. In otherwords, a potential solution must prove that computing resources weredrained in solving the problem. In some types of permissionlessblockchains, miners may be rewarded with value (e.g., coins, etc.) forcorrectly mining a block.

Here, the PoW process, alongside the chaining of blocks, makesmodifications of the blockchain extremely difficult, as an attacker mustmodify all subsequent blocks in order for the modifications of one blockto be accepted. Furthermore, as new blocks are mined, the difficulty ofmodifying a block increases, and the number of subsequent blocksincreases. With distribution 366, the successfully validated block isdistributed through the permissionless blockchain 352 and all nodes 354add the block to a majority chain which is the permissionlessblockchain's 352 auditable ledger. Furthermore, the value in thetransaction submitted by the sender 356 is deposited or otherwisetransferred to the digital wallet of the recipient device 358.

FIG. 4A illustrates a flow diagram 400 of an example method ofcomputation, verification and prediction of a linked access inblockchain networks, according to example embodiments. Referring to FIG.4A, the method 400 may include one or more of the steps described below.

FIG. 4A illustrates a flow chart of an example method executed by themodeling node 102 (see FIG. 1A). It should be understood that method 400depicted in FIG. 4A may include additional operations and that some ofthe operations described therein may be removed and/or modified withoutdeparting from the scope of the method 400. The description of themethod 400 is also made with reference to the features depicted in FIG.1A for purposes of illustration. Particularly, the processor 104 of themodeling node 102 may execute some or all of the operations included inthe method 400.

With reference to FIG. 4A, at block 412, the processor 104 may traversea supply-chain downstream from an initial step. At block 414, theprocessor 104 may detect a multi-organization step. At block 416, theprocessor 104 may, responsive to the detection of the multi-organizationstep, execute a branch prediction algorithm to determine downstreamgranted organizations.

FIG. 4B illustrates a flow diagram 450 of an example method, accordingto example embodiments. Referring to FIG. 4B, the method 450 may alsoinclude one or more of the following steps. At block 452, the processor104 may traverse a master level data graph upstream from the initialstep to the multi-organization step. At block 454, the processor 104 mayexecute the branch prediction algorithm to determine a plurality ofdocuments to be updated based on the traversing of the master level datagraph. At block 456, the processor 104 may update the plurality of thedocuments by current grants. Note that the supply-chain may be a linearsupply-chain, wherein each step comprises one organization. Also notethat the supply-chain may comprise a plurality of linear subsections. Atblock 458, the processor 104 may minimize a number of traversals of thesupply-chain and a number of updates of a plurality of documents basedon the plurality of the linear subsections of the supply-chain.

FIG. 4C illustrates a flow diagram 460 of an example method ofcomputation, verification and prediction of a linked access inblockchain networks, according to example embodiments. Referring to FIG.4C, the method 460 may include one or more of the steps described below.

FIG. 4C illustrates a flow chart of an example method executed by themodeling node 102 (see FIG. 1B). It should be understood that method 460depicted in FIG. 4C may include additional operations and that some ofthe operations described therein may be removed and/or modified withoutdeparting from the scope of the method 460. The description of themethod 460 is also made with reference to the features depicted in FIG.1B for purposes of illustration. Particularly, the processor 104 of themodeling node 102 may execute some or all of the operations included inthe method 460.

With reference to FIG. 4C, at block 462, the processor 104 may detect afork in a supply-chain. At block 464, the processor 104 may resolve abranch prediction to determine a likely access control. At block 466,the processor 104 may generate a range of information based on a branchconfidence level. At block 468, the processor 104 may, responsive to theresolution of the branch prediction, revoke access from a document orgrant a greater access to the document based on the range.

FIG. 4D illustrates a flow diagram 470 of an example method, accordingto example embodiments. Referring to FIG. 4D, the method 470 may alsoinclude one or more of the following steps. At block 472, the processor104 may grant low-risk data based on a low confidence. At block 474, theprocessor 104 may grant high-risk data based on a high confidence. Atblock 476, the processor 104 may determine the range based on thesupply-chain and participating nodes representing organizations. Atblock 478, the processor 104 may process an input from the organizationsto determine the range of one or more types of data of the range ofinformation. At block 480, the processor 104 may, in response to anincorrect branch prediction, revoke a document. At block 482, theprocessor 104 may, in response to a correct branch prediction, reveal afull document.

FIG. 5A illustrates an example system 500 that includes a physicalinfrastructure 510 configured to perform various operations according toexample embodiments. Referring to FIG. 5A, the physical infrastructure510 includes a module 512 and a module 514. The module 514 includes ablockchain 520 and a smart contract 530 (which may reside on theblockchain 520), that may execute any of the operational steps 508 (inmodule 512) included in any of the example embodiments. Thesteps/operations 508 may include one or more of the embodimentsdescribed or depicted and may represent output or written informationthat is written or read from one or more smart contracts 530 and/orblockchains 520. The physical infrastructure 510, the module 512, andthe module 514 may include one or more computers, servers, processors,memories, and/or wireless communication devices. Further, the module 512and the module 514 may be a same module.

FIG. 5B illustrates another example system 540 configured to performvarious operations according to example embodiments. Referring to FIG.5B, the system 540 includes a module 512 and a module 514. The module514 includes a blockchain 520 and a smart contract 530 (which may resideon the blockchain 520), that may execute any of the operational steps508 (in module 512) included in any of the example embodiments. Thesteps/operations 508 may include one or more of the embodimentsdescribed or depicted and may represent output or written informationthat is written or read from one or more smart contracts 530 and/orblockchains 520. The module 512 and the module 514 may include one ormore computers, servers, processors, memories, and/or wirelesscommunication devices. Further, the module 512 and the module 514 may bea same module.

FIG. 5C illustrates an example system configured to utilize a smartcontract configuration among contracting parties and a mediating serverconfigured to enforce the smart contract terms on the blockchainaccording to example embodiments. Referring to FIG. 5C, theconfiguration 550 may represent a communication session, an assettransfer session or a process or procedure that is driven by a smartcontract 530 which explicitly identifies one or more user devices 552and/or 556. The execution, operations and results of the smart contractexecution may be managed by a server 554. Content of the smart contract530 may require digital signatures by one or more of the entities 552and 556 which are parties to the smart contract transaction. The resultsof the smart contract execution may be written to a blockchain 520 as ablockchain transaction. The smart contract 530 resides on the blockchain520 which may reside on one or more computers, servers, processors,memories, and/or wireless communication devices.

FIG. 5D illustrates a system 560 including a blockchain, according toexample embodiments. Referring to the example of FIG. 5D, an applicationprogramming interface (API) gateway 562 provides a common interface foraccessing blockchain logic (e.g., smart contract 530 or other chaincode)and data (e.g., distributed ledger, etc.). In this example, the APIgateway 562 is a common interface for performing transactions (invoke,queries, etc.) on the blockchain by connecting one or more entities 552and 556 to a blockchain peer (i.e., server 554). Here, the server 554 isa blockchain network peer component that holds a copy of the world stateand a distributed ledger allowing clients 552 and 556 to query data onthe world state as well as submit transactions into the blockchainnetwork where, depending on the smart contract 530 and endorsementpolicy, endorsing peers will run the smart contracts 530.

The above embodiments may be implemented in hardware, in a computerprogram executed by a processor, in firmware, or in a combination of theabove. A computer program may be embodied on a computer readable medium,such as a storage medium. For example, a computer program may reside inrandom access memory (“RAM”), flash memory, read-only memory (“ROM”),erasable programmable read-only memory (“EPROM”), electrically erasableprogrammable read-only memory (“EEPROM”), registers, hard disk, aremovable disk, a compact disk read-only memory (“CD-ROM”), or any otherform of storage medium known in the art.

An exemplary storage medium may be coupled to the processor such thatthe processor may read information from, and write information to, thestorage medium. In the alternative, the storage medium may be integralto the processor. The processor and the storage medium may reside in anapplication specific integrated circuit (“ASIC”). In the alternative,the processor and the storage medium may reside as discrete components.

FIG. 6A illustrates a process 600 of a new block being added to adistributed ledger 620, according to example embodiments, and FIG. 6Billustrates contents of a new data block structure 630 for blockchain,according to example embodiments. The new data block 630 may containsupply-chain grants data.

Referring to FIG. 6A, clients (not shown) may submit transactions toblockchain nodes 611, 612, and/or 613. Clients may be instructionsreceived from any source to enact activity on the blockchain 620. As anexample, clients may be applications that act on behalf of a requester,such as a device, person or entity to propose transactions for theblockchain. The plurality of blockchain peers (e.g., blockchain nodes611, 612, and 613) may maintain a state of the blockchain network and acopy of the distributed ledger 620. Different types of blockchainnodes/peers may be present in the blockchain network including endorsingpeers which simulate and endorse transactions proposed by clients andcommitting peers which verify endorsements, validate transactions, andcommit transactions to the distributed ledger 620. In this example, theblockchain nodes 611, 612, and 613 may perform the role of endorsernode, committer node, or both.

The distributed ledger 620 includes a blockchain which stores immutable,sequenced records in blocks, and a state database 624 (current worldstate) maintaining a current state of the blockchain 622. Onedistributed ledger 620 may exist per channel and each peer maintains itsown copy of the distributed ledger 620 for each channel of which theyare a member. The blockchain 622 is a transaction log, structured ashash-linked blocks where each block contains a sequence of Ntransactions. Blocks may include various components such as shown inFIG. 6B. The linking of the blocks (shown by arrows in FIG. 6A) may begenerated by adding a hash of a prior block's header within a blockheader of a current block. In this way, all transactions on theblockchain 622 are sequenced and cryptographically linked togetherpreventing tampering with blockchain data without breaking the hashlinks. Furthermore, because of the links, the latest block in theblockchain 622 represents every transaction that has come before it. Theblockchain 622 may be stored on a peer file system (local or attachedstorage), which supports an append-only blockchain workload.

The current state of the blockchain 622 and the distributed ledger 622may be stored in the state database 624. Here, the current state datarepresents the latest values for all keys ever included in the chaintransaction log of the blockchain 622. Chaincode invocations executetransactions against the current state in the state database 624. Tomake these chaincode interactions extremely efficient, the latest valuesof all keys are stored in the state database 624. The state database 624may include an indexed view into the transaction log of the blockchain622, it can therefore be regenerated from the chain at any time. Thestate database 624 may automatically get recovered (or generated ifneeded) upon peer startup, before transactions are accepted.

Endorsing nodes receive transactions from clients and endorse thetransaction based on simulated results. Endorsing nodes hold smartcontracts which simulate the transaction proposals. When an endorsingnode endorses a transaction, the endorsing node creates a transactionendorsement which is a signed response from the endorsing node to theclient application indicating the endorsement of the simulatedtransaction. The method of endorsing a transaction depends on anendorsement policy which may be specified within chaincode. An exampleof an endorsement policy is “the majority of endorsing peers mustendorse the transaction”. Different channels may have differentendorsement policies. Endorsed transactions are forward by the clientapplication to ordering service 610.

The ordering service 610 accepts endorsed transactions, orders them intoa block, and delivers the blocks to the committing peers. For example,the ordering service 610 may initiate a new block when a threshold oftransactions has been reached, a timer times out, or another condition.In the example of FIG. 6A, blockchain node 612 is a committing peer thathas received a new data new data block 630 for storage on blockchain620. The first block in the blockchain may be referred to as a genesisblock which includes information about the blockchain, its members, thedata stored therein, etc.

The ordering service 610 may be made up of a cluster of orderers. Theordering service 610 does not process transactions, smart contracts, ormaintain the shared ledger. Rather, the ordering service 610 may acceptthe endorsed transactions and specifies the order in which thosetransactions are committed to the distributed ledger 620. Thearchitecture of the blockchain network may be designed such that thespecific implementation of ‘ordering’ (e.g., Solo, Kafka, BFT, etc.)becomes a pluggable component.

Transactions are written to the distributed ledger 620 in a consistentorder. The order of transactions is established to ensure that theupdates to the state database 624 are valid when they are committed tothe network. Unlike a cryptocurrency blockchain system (e.g., Bitcoin,etc.) where ordering occurs through the solving of a cryptographicpuzzle, or mining, in this example the parties of the distributed ledger620 may choose the ordering mechanism that best suits that network.

When the ordering service 610 initializes a new data block 630, the newdata block 630 may be broadcast to committing peers (e.g., blockchainnodes 611, 612, and 613). In response, each committing peer validatesthe transaction within the new data block 630 by checking to make surethat the read set and the write set still match the current world statein the state database 624. Specifically, the committing peer candetermine whether the read data that existed when the endorserssimulated the transaction is identical to the current world state in thestate database 624. When the committing peer validates the transaction,the transaction is written to the blockchain 622 on the distributedledger 620, and the state database 624 is updated with the write datafrom the read-write set. If a transaction fails, that is, if thecommitting peer finds that the read-write set does not match the currentworld state in the state database 624, the transaction ordered into ablock will still be included in that block, but it will be marked asinvalid, and the state database 624 will not be updated.

Referring to FIG. 6B, a new data block 630 (also referred to as a datablock) that is stored on the blockchain 622 of the distributed ledger620 may include multiple data segments such as a block header 640, blockdata 650, and block metadata 660. It should be appreciated that thevarious depicted blocks and their contents, such as new data block 630and its contents. Shown in FIG. 6B are merely examples and are not meantto limit the scope of the example embodiments. The new data block 630may store transactional information of N transaction(s) (e.g., 1, 10,100, 500, 1000, 2000, 3000, etc.) within the block data 650. The newdata block 630 may also include a link to a previous block (e.g., on theblockchain 622 in FIG. 6A) within the block header 640. In particular,the block header 640 may include a hash of a previous block's header.The block header 640 may also include a unique block number, a hash ofthe block data 650 of the new data block 630, and the like. The blocknumber of the new data block 630 may be unique and assigned in variousorders, such as an incremental/sequential order starting from zero.

The block data 650 may store transactional information of eachtransaction that is recorded within the new data block 630. For example,the transaction data may include one or more of a type of thetransaction, a version, a timestamp, a channel ID of the distributedledger 620, a transaction ID, an epoch, a payload visibility, achaincode path (deploy tx), a chaincode name, a chaincode version, input(chaincode and functions), a client (creator) identify such as a publickey and certificate, a signature of the client, identities of endorsers,endorser signatures, a proposal hash, chaincode events, response status,namespace, a read set (list of key and version read by the transaction,etc.), a write set (list of key and value, etc.), a start key, an endkey, a list of keys, a Merkel tree query summary, and the like. Thetransaction data may be stored for each of the N transactions.

In some embodiments, the block data 650 may also store new data 662which adds additional information to the hash-linked chain of blocks inthe blockchain 622. The additional information includes one or more ofthe steps, features, processes and/or actions described or depictedherein. Accordingly, the new data 662 can be stored in an immutable logof blocks on the distributed ledger 620. Some of the benefits of storingsuch new data 662 are reflected in the various embodiments disclosed anddepicted herein. Although in FIG. 6B the new data 662 is depicted in theblock data 650 but could also be located in the block header 640 or theblock metadata 660. The new data 662 may include supply-chain grantsdata.

The block metadata 660 may store multiple fields of metadata (e.g., as abyte array, etc.). Metadata fields may include signature on blockcreation, a reference to a last configuration block, a transactionfilter identifying valid and invalid transactions within the block, lastoffset persisted of an ordering service that ordered the block, and thelike. The signature, the last configuration block, and the orderermetadata may be added by the ordering service 610. Meanwhile, acommitter of the block (such as blockchain node 612) may addvalidity/invalidity information based on an endorsement policy,verification of read/write sets, and the like. The transaction filtermay include a byte array of a size equal to the number of transactionsin the block data 650 and a validation code identifying whether atransaction was valid/invalid.

FIG. 6C illustrates an embodiment of a blockchain 670 for digitalcontent in accordance with the embodiments described herein. The digitalcontent may include one or more files and associated information. Thefiles may include media, images, video, audio, text, links, graphics,animations, web pages, documents, or other forms of digital content. Theimmutable, append-only aspects of the blockchain serve as a safeguard toprotect the integrity, validity, and authenticity of the digitalcontent, making it suitable use in legal proceedings where admissibilityrules apply or other settings where evidence is taken in toconsideration or where the presentation and use of digital informationis otherwise of interest. In this case, the digital content may bereferred to as digital evidence.

The blockchain may be formed in various ways. In one embodiment, thedigital content may be included in and accessed from the blockchainitself. For example, each block of the blockchain may store a hash valueof reference information (e.g., header, value, etc.) along theassociated digital content. The hash value and associated digitalcontent may then be encrypted together. Thus, the digital content ofeach block may be accessed by decrypting each block in the blockchain,and the hash value of each block may be used as a basis to reference aprevious block. This may be illustrated as follows:

Block 1 Block 2 . . . Block N Hash Value 1 Hash Value 2 Hash Value NDigital Content 1 Digital Content 2 Digital Content N

In one embodiment, the digital content may be not included in theblockchain. For example, the blockchain may store the encrypted hashesof the content of each block without any of the digital content. Thedigital content may be stored in another storage area or memory addressin association with the hash value of the original file. The otherstorage area may be the same storage device used to store the blockchainor may be a different storage area or even a separate relationaldatabase. The digital content of each block may be referenced oraccessed by obtaining or querying the hash value of a block of interestand then looking up that has value in the storage area, which is storedin correspondence with the actual digital content. This operation may beperformed, for example, a database gatekeeper. This may be illustratedas follows:

Blockchain Storage Area Block 1 Hash Value Block 1 Hash Value . . .Content . . . . . . Block N Hash Value Block N Hash Value . . . Content

In the example embodiment of FIG. 6C, the blockchain 670 includes anumber of blocks 678 ₁, 678 ₂, . . . 678 _(N) cryptographically linkedin an ordered sequence, where N≥1. The encryption used to link theblocks 678 ₁, 678 ₂, . . . 678 _(N) may be any of a number of keyed orun-keyed Hash functions. In one embodiment, the blocks 678 ₁, 678 ₂, . .. 678 _(N) are subject to a hash function which produces n-bitalphanumeric outputs (where n is 256 or another number) from inputs thatare based on information in the blocks. Examples of such a hash functioninclude, but are not limited to, a SHA-type (SHA stands for Secured HashAlgorithm) algorithm, Merkle-Damgard algorithm, HAIFA algorithm,Merkle-tree algorithm, nonce-based algorithm, and anon-collision-resistant PRF algorithm. In another embodiment, the blocks678 ₁, 678 ₂, . . . , 678 _(N) may be cryptographically linked by afunction that is different from a hash function. For purposes ofillustration, the following description is made with reference to a hashfunction, e.g., SHA-2.

Each of the blocks 678 ₁, 678 ₂, . . . , 678 _(N) in the blockchainincludes a header, a version of the file, and a value. The header andthe value are different for each block as a result of hashing in theblockchain. In one embodiment, the value may be included in the header.As described in greater detail below, the version of the file may be theoriginal file or a different version of the original file.

The first block 678 ₁ in the blockchain is referred to as the genesisblock and includes the header 672 ₁, original file 674 ₁, and an initialvalue 676 ₁. The hashing scheme used for the genesis block, and indeedin all subsequent blocks, may vary. For example, all the information inthe first block 678 ₁ may be hashed together and at one time, or each ora portion of the information in the first block 678 ₁ may be separatelyhashed and then a hash of the separately hashed portions may beperformed.

The header 672 ₁ may include one or more initial parameters, which, forexample, may include a version number, timestamp, nonce, rootinformation, difficulty level, consensus protocol, duration, mediaformat, source, descriptive keywords, and/or other informationassociated with original file 674 ₁ and/or the blockchain. The header672 ₁ may be generated automatically (e.g., by blockchain networkmanaging software) or manually by a blockchain participant. Unlike theheader in other blocks 678 ₂ to 678 _(N) in the blockchain, the header672 ₁ in the genesis block does not reference a previous block, simplybecause there is no previous block.

The original file 674 ₁ in the genesis block may be, for example, dataas captured by a device with or without processing prior to itsinclusion in the blockchain. The original file 674 ₁ is received throughthe interface of the system from the device, media source, or node. Theoriginal file 674 ₁ is associated with metadata, which, for example, maybe generated by a user, the device, and/or the system processor, eithermanually or automatically. The metadata may be included in the firstblock 678 ₁ in association with the original file 674 ₁.

The value 676 ₁ in the genesis block is an initial value generated basedon one or more unique attributes of the original file 674 ₁. In oneembodiment, the one or more unique attributes may include the hash valuefor the original file 674 ₁, metadata for the original file 674 ₁, andother information associated with the file. In one implementation, theinitial value 676 ₁ may be based on the following unique attributes:

-   -   1) SHA-2 computed hash value for the original file    -   2) originating device ID    -   3) starting timestamp for the original file    -   4) initial storage location of the original file    -   5) blockchain network member ID for software to currently        control the original file and associated metadata

The other blocks 678 ₂ to 678 _(N) in the blockchain also have headers,files, and values. However, unlike the first block 672 ₁, each of theheaders 672 ₂ to 672 _(N) in the other blocks includes the hash value ofan immediately preceding block. The hash value of the immediatelypreceding block may be just the hash of the header of the previous blockor may be the hash value of the entire previous block. By including thehash value of a preceding block in each of the remaining blocks, a tracecan be performed from the Nth block back to the genesis block (and theassociated original file) on a block-by-block basis, as indicated byarrows 680, to establish an auditable and immutable chain-of-custody.

Each of the header 672 ₂ to 672 _(N) in the other blocks may alsoinclude other information, e.g., version number, timestamp, nonce, rootinformation, difficulty level, consensus protocol, and/or otherparameters or information associated with the corresponding files and/orthe blockchain in general.

The files 674 ₂ to 674 _(N) in the other blocks may be equal to theoriginal file or may be a modified version of the original file in thegenesis block depending, for example, on the type of processingperformed. The type of processing performed may vary from block toblock. The processing may involve, for example, any modification of afile in a preceding block, such as redacting information or otherwisechanging the content of, taking information away from, or adding orappending information to the files.

Additionally, or alternatively, the processing may involve merelycopying the file from a preceding block, changing a storage location ofthe file, analyzing the file from one or more preceding blocks, movingthe file from one storage or memory location to another, or performingaction relative to the file of the blockchain and/or its associatedmetadata. Processing which involves analyzing a file may include, forexample, appending, including, or otherwise associating variousanalytics, statistics, or other information associated with the file.

The values in each of the other blocks 676 ₂ to 676 _(N) in the otherblocks are unique values and are all different as a result of theprocessing performed. For example, the value in any one blockcorresponds to an updated version of the value in the previous block.The update is reflected in the hash of the block to which the value isassigned. The values of the blocks therefore provide an indication ofwhat processing was performed in the blocks and also permit a tracingthrough the blockchain back to the original file. This tracking confirmsthe chain-of-custody of the file throughout the entire blockchain.

For example, consider the case where portions of the file in a previousblock are redacted, blocked out, or pixelated in order to protect theidentity of a person shown in the file. In this case, the blockincluding the redacted file will include metadata associated with theredacted file, e.g., how the redaction was performed, who performed theredaction, timestamps where the redaction(s) occurred, etc. The metadatamay be hashed to form the value. Because the metadata for the block isdifferent from the information that was hashed to form the value in theprevious block, the values are different from one another and may berecovered when decrypted.

In one embodiment, the value of a previous block may be updated (e.g., anew hash value computed) to form the value of a current block when anyone or more of the following occurs. The new hash value may be computedby hashing all or a portion of the information noted below, in thisexample embodiment.

-   -   a) new SHA-2 computed hash value if the file has been processed        in any way (e.g., if the file was redacted, copied, altered,        accessed, or some other action was taken)    -   b) new storage location for the file    -   c) new metadata identified associated with the file    -   d) transfer of access or control of the file from one blockchain        participant to another blockchain participant

FIG. 6D illustrates an embodiment of a block which may represent thestructure of the blocks in the blockchain 690 in accordance with oneembodiment. The block, Block_(i), includes a header 672 _(i), a file 674_(i), and a value 676 _(i).

The header 672 _(i) includes a hash value of a previous blockBlock_(i-1) and additional reference information, which, for example,may be any of the types of information (e.g., header informationincluding references, characteristics, parameters, etc.) discussedherein. All blocks reference the hash of a previous block except, ofcourse, the genesis block. The hash value of the previous block may bejust a hash of the header in the previous block or a hash of all or aportion of the information in the previous block, including the file andmetadata.

The file 674 _(i) includes a plurality of data, such as Data 1, Data 2,. . . , Data N in sequence. The data are tagged with metadata Metadata1, Metadata 2, . . . , Metadata N which describe the content and/orcharacteristics associated with the data. For example, the metadata foreach data may include information to indicate a timestamp for the data,process the data, keywords indicating the persons or other contentdepicted in the data, and/or other features that may be helpful toestablish the validity and content of the file as a whole, andparticularly its use a digital evidence, for example, as described inconnection with an embodiment discussed below. In addition to themetadata, each data may be tagged with reference REF₁, REF₂, . . . ,REF_(N) to a previous data to prevent tampering, gaps in the file, andsequential reference through the file.

Once the metadata is assigned to the data (e.g., through a smartcontract), the metadata cannot be altered without the hash changing,which can easily be identified for invalidation. The metadata, thus,creates a data log of information that may be accessed for use byparticipants in the blockchain.

The value 676 _(i) is a hash value or other value computed based on anyof the types of information previously discussed. For example, for anygiven block Block_(i), the value for that block may be updated toreflect the processing that was performed for that block, e.g., new hashvalue, new storage location, new metadata for the associated file,transfer of control or access, identifier, or other action orinformation to be added. Although the value in each block is shown to beseparate from the metadata for the data of the file and header, thevalue may be based, in part or whole, on this metadata in anotherembodiment.

Once the blockchain 670 is formed, at any point in time, the immutablechain-of-custody for the file may be obtained by querying the blockchainfor the transaction history of the values across the blocks. This query,or tracking procedure, may begin with decrypting the value of the blockthat is most currently included (e.g., the last (N^(th)) block), andthen continuing to decrypt the value of the other blocks until thegenesis block is reached and the original file is recovered. Thedecryption may involve decrypting the headers and files and associatedmetadata at each block, as well.

Decryption is performed based on the type of encryption that took placein each block. This may involve the use of private keys, public keys, ora public key-private key pair. For example, when asymmetric encryptionis used, blockchain participants or a processor in the network maygenerate a public key and private key pair using a predeterminedalgorithm. The public key and private key are associated with each otherthrough some mathematical relationship. The public key may bedistributed publicly to serve as an address to receive messages fromother users, e.g., an IP address or home address. The private key iskept secret and used to digitally sign messages sent to other blockchainparticipants. The signature is included in the message so that therecipient can verify using the public key of the sender. This way, therecipient can be sure that only the sender could have sent this message.

Generating a key pair may be analogous to creating an account on theblockchain, but without having to actually register anywhere. Also,every transaction that is executed on the blockchain is digitally signedby the sender using their private key. This signature ensures that onlythe owner of the account can track and process (if within the scope ofpermission determined by a smart contract) the file of the blockchain.

FIGS. 7A and 7B illustrate additional examples of use cases forblockchain which may be incorporated and used herein. In particular,FIG. 7A illustrates an example 700 of a blockchain 710 which storesmachine learning (artificial intelligence) data. Machine learning relieson vast quantities of historical data (or training data) to buildpredictive models for accurate prediction on new data. Machine learningsoftware (e.g., neural networks, etc.) can often sift through millionsof records to unearth non-intuitive patterns.

In the example of FIG. 7A, a host platform 720 builds and deploys amachine learning model for predictive monitoring of assets 730. Here,the host platform 720 may be a cloud platform, an industrial server, aweb server, a personal computer, a user device, and the like. Assets 730can be any type of asset (e.g., machine or equipment, etc.) such as anaircraft, locomotive, turbine, medical machinery and equipment, oil andgas equipment, boats, ships, vehicles, and the like. As another example,assets 730 may be non-tangible assets such as stocks, currency, digitalcoins, insurance, or the like.

The blockchain 710 can be used to significantly improve both a trainingprocess 702 of the machine learning model and a predictive process 704based on a trained machine learning model. For example, in 702, ratherthan requiring a data scientist / engineer or other user to collect thedata, historical data may be stored by the assets 730 themselves (orthrough an intermediary, not shown) on the blockchain 710. This cansignificantly reduce the collection time needed by the host platform 720when performing predictive model training. For example, using smartcontracts, data can be directly and reliably transferred straight fromits place of origin to the blockchain 710. By using the blockchain 710to ensure the security and ownership of the collected data, smartcontracts may directly send the data from the assets to the individualsthat use the data for building a machine learning model. This allows forsharing of data among the assets 730.

The collected data may be stored in the blockchain 710 based on aconsensus mechanism. The consensus mechanism pulls in (permissionednodes) to ensure that the data being recorded is verified and accurate.The data recorded is time-stamped, cryptographically signed, andimmutable. It is therefore auditable, transparent, and secure. AddingIoT devices which write directly to the blockchain can, in certain cases(i.e. supply chain, healthcare, logistics, etc.), increase both thefrequency and accuracy of the data being recorded.

Furthermore, training of the machine learning model on the collecteddata may take rounds of refinement and testing by the host platform 720.Each round may be based on additional data or data that was notpreviously considered to help expand the knowledge of the machinelearning model. In 702, the different training and testing steps (andthe data associated therewith) may be stored on the blockchain 710 bythe host platform 720. Each refinement of the machine learning model(e.g., changes in variables, weights, etc.) may be stored on theblockchain 710. This provides verifiable proof of how the model wastrained and what data was used to train the model. Furthermore, when thehost platform 720 has achieved a finally trained model, the resultingmodel may be stored on the blockchain 710.

After the model has been trained, it may be deployed to a liveenvironment where it can make predictions/decisions based on theexecution of the final trained machine learning model. For example, in704, the machine learning model may be used for condition-basedmaintenance (CBM) for an asset such as an aircraft, a wind turbine, ahealthcare machine, and the like. In this example, data fed back fromthe asset 730 may be input the machine learning model and used to makeevent predictions such as failure events, error codes, and the like.Determinations made by the execution of the machine learning model atthe host platform 720 may be stored on the blockchain 710 to provideauditable/verifiable proof. As one non-limiting example, the machinelearning model may predict a future breakdown/failure to a part of theasset 730 and create alert or a notification to replace the part. Thedata behind this decision may be stored by the host platform 720 on theblockchain 710. In one embodiment the features and/or the actionsdescribed and/or depicted herein can occur on or with respect to theblockchain 710.

New transactions for a blockchain can be gathered together into a newblock and added to an existing hash value. This is then encrypted tocreate a new hash for the new block. This is added to the next list oftransactions when they are encrypted, and so on. The result is a chainof blocks that each contain the hash values of all preceding blocks.Computers that store these blocks regularly compare their hash values toensure that they are all in agreement. Any computer that does not agree,discards the records that are causing the problem. This approach is goodfor ensuring tamper-resistance of the blockchain, but it is not perfect.

One way to game this system is for a dishonest user to change the listof transactions in their favor, but in a way that leaves the hashunchanged. This can be done by brute force, in other words by changing arecord, encrypting the result, and seeing whether the hash value is thesame. And if not, trying again and again and again until it finds a hashthat matches. The security of blockchains is based on the belief thatordinary computers can only perform this kind of brute force attack overtime scales that are entirely impractical, such as the age of theuniverse. By contrast, quantum computers are much faster (1000s of timesfaster) and consequently pose a much greater threat.

FIG. 7B illustrates an example 750 of a quantum-secure blockchain 752which implements quantum key distribution (QKD) to protect against aquantum computing attack. In this example, blockchain users can verifyeach other's identities using QKD. This sends information using quantumparticles such as photons, which cannot be copied by an eavesdropperwithout destroying them. In this way, a sender and a receiver throughthe blockchain can be sure of each other's identity.

In the example of FIG. 7B, four users are present 754, 756, 758, and760. Each of pair of users may share a secret key 762 (i.e., a QKD)between themselves. Since there are four nodes in this example, sixpairs of nodes exist, and therefore six different secret keys 762 areused including QKD_(AB), QKD_(AC), QKD_(AD), QKD_(BC), QKD_(BD), andQKD_(CD). Each pair can create a QKD by sending information usingquantum particles such as photons, which cannot be copied by aneavesdropper without destroying them. In this way, a pair of users canbe sure of each other's identity.

The operation of the blockchain 752 is based on two procedures (i)creation of transactions, and (ii) construction of blocks that aggregatethe new transactions. New transactions may be created similar to atraditional blockchain network. Each transaction may contain informationabout a sender, a receiver, a time of creation, an amount (or value) tobe transferred, a list of reference transactions that justifies thesender has funds for the operation, and the like. This transactionrecord is then sent to all other nodes where it is entered into a poolof unconfirmed transactions. Here, two parties (i.e., a pair of usersfrom among 754-760) authenticate the transaction by providing theirshared secret key 762 (QKD). This quantum signature can be attached toevery transaction making it exceedingly difficult to tamper with. Eachnode checks their entries with respect to a local copy of the blockchain752 to verify that each transaction has sufficient funds. However, thetransactions are not yet confirmed.

Rather than perform a traditional mining process on the blocks, theblocks may be created in a decentralized manner using a broadcastprotocol. At a predetermined period of time (e.g., seconds, minutes,hours, etc.) the network may apply the broadcast protocol to anyunconfirmed transaction thereby to achieve a Byzantine agreement(consensus) regarding a correct version of the transaction. For example,each node may possess a private value (transaction data of thatparticular node). In a first round, nodes transmit their private valuesto each other. In subsequent rounds, nodes communicate the informationthey received in the previous round from other nodes. Here, honest nodesare able to create a complete set of transactions within a new block.This new block can be added to the blockchain 752. In one embodiment thefeatures and/or the actions described and/or depicted herein can occuron or with respect to the blockchain 752.

FIG. 8 illustrates an example system 800 that supports one or more ofthe example embodiments described and/or depicted herein. The system 800comprises a computer system/server 802, which is operational withnumerous other general purpose or special purpose computing systemenvironments or configurations. Examples of well-known computingsystems, environments, and/or configurations that may be suitable foruse with computer system/server 802 include, but are not limited to,personal computer systems, server computer systems, thin clients, thickclients, hand-held or laptop devices, multiprocessor systems,microprocessor-based systems, set top boxes, programmable consumerelectronics, network PCs, minicomputer systems, mainframe computersystems, and distributed cloud computing environments that include anyof the above systems or devices, and the like.

Computer system/server 802 may be described in the general context ofcomputer system-executable instructions, such as program modules, beingexecuted by a computer system. Generally, program modules may includeroutines, programs, objects, components, logic, data structures, and soon that perform particular tasks or implement particular abstract datatypes. Computer system/server 802 may be practiced in distributed cloudcomputing environments where tasks are performed by remote processingdevices that are linked through a communications network. In adistributed cloud computing environment, program modules may be locatedin both local and remote computer system storage media including memorystorage devices.

As shown in FIG. 8, computer system/server 802 in cloud computing node800 is shown in the form of a general-purpose computing device. Thecomponents of computer system/server 802 may include, but are notlimited to, one or more processors or processing units 804, a systemmemory 806, and a bus that couples various system components includingsystem memory 806 to processor 804.

The bus represents one or more of any of several types of busstructures, including a memory bus or memory controller, a peripheralbus, an accelerated graphics port, and a processor or local bus usingany of a variety of bus architectures. By way of example, and notlimitation, such architectures include Industry Standard Architecture(ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA)bus, Video Electronics Standards Association (VESA) local bus, andPeripheral Component Interconnects (PCI) bus.

Computer system/server 802 typically includes a variety of computersystem readable media. Such media may be any available media that isaccessible by computer system/server 802, and it includes both volatileand non-volatile media, removable and non-removable media. System memory806, in one embodiment, implements the flow diagrams of the otherfigures. The system memory 806 can include computer system readablemedia in the form of volatile memory, such as random-access memory (RAM)810 and/or cache memory 812. Computer system/server 802 may furtherinclude other removable/non-removable, volatile/non-volatile computersystem storage media. By way of example only, storage system 814 can beprovided for reading from and writing to a non-removable, non-volatilemagnetic media (not shown and typically called a “hard drive”). Althoughnot shown, a magnetic disk drive for reading from and writing to aremovable, non-volatile magnetic disk (e.g., a “floppy disk”), and anoptical disk drive for reading from or writing to a removable,non-volatile optical disk such as a CD-ROM, DVD-ROM or other opticalmedia can be provided. In such instances, each can be connected to thebus by one or more data media interfaces. As will be further depictedand described below, memory 806 may include at least one program producthaving a set (e.g., at least one) of program modules that are configuredto carry out the functions of various embodiments of the application.

Program/utility 816, having a set (at least one) of program modules 818,may be stored in memory 806 by way of example, and not limitation, aswell as an operating system, one or more application programs, otherprogram modules, and program data. Each of the operating system, one ormore application programs, other program modules, and program data orsome combination thereof, may include an implementation of a networkingenvironment. Program modules 818 generally carry out the functionsand/or methodologies of various embodiments of the application asdescribed herein.

As will be appreciated by one skilled in the art, aspects of the presentapplication may be embodied as a system, method, or computer programproduct. Accordingly, aspects of the present application may take theform of an entirely hardware embodiment, an entirely software embodiment(including firmware, resident software, micro-code, etc.) or anembodiment combining software and hardware aspects that may allgenerally be referred to herein as a “circuit,” “module” or “system.”Furthermore, aspects of the present application may take the form of acomputer program product embodied in one or more computer readablemedium(s) having computer readable program code embodied thereon.

Computer system/server 802 may also communicate with one or moreexternal devices 820 such as a keyboard, a pointing device, a display822, etc.; one or more devices that enable a user to interact withcomputer system/server 802; and/or any devices (e.g., network card,modem, etc.) that enable computer system/server 802 to communicate withone or more other computing devices. Such communication can occur viaI/O interfaces 824. Still yet, computer system/server 802 cancommunicate with one or more networks such as a local area network(LAN), a general wide area network (WAN), and/or a public network (e.g.,the Internet) via network adapter 826. As depicted, network adapter 826communicates with the other components of computer system/server 802 viaa bus. It should be understood that although not shown, other hardwareand/or software components could be used in conjunction with computersystem/server 802. Examples, include, but are not limited to: microcode,device drivers, redundant processing units, external disk drive arrays,RAID systems, tape drives, and data archival storage systems, etc.

Although an exemplary embodiment of at least one of a system, method,and non-transitory computer readable medium has been illustrated in theaccompanied drawings and described in the foregoing detaileddescription, it will be understood that the application is not limitedto the embodiments disclosed, but is capable of numerous rearrangements,modifications, and substitutions as set forth and defined by thefollowing claims. For example, the capabilities of the system of thevarious figures can be performed by one or more of the modules orcomponents described herein or in a distributed architecture and mayinclude a transmitter, receiver or pair of both. For example, all orpart of the functionality performed by the individual modules, may beperformed by one or more of these modules. Further, the functionalitydescribed herein may be performed at various times and in relation tovarious events, internal or external to the modules or components. Also,the information sent between various modules can be sent between themodules via at least one of: a data network, the Internet, a voicenetwork, an Internet Protocol network, a wireless device, a wired deviceand/or via plurality of protocols. Also, the messages sent or receivedby any of the modules may be sent or received directly and/or via one ormore of the other modules.

One skilled in the art will appreciate that a “system” could be embodiedas a personal computer, a server, a console, a personal digitalassistant (PDA), a cell phone, a tablet computing device, a smartphoneor any other suitable computing device, or combination of devices.Presenting the above-described functions as being performed by a“system” is not intended to limit the scope of the present applicationin any way but is intended to provide one example of many embodiments.Indeed, methods, systems and apparatuses disclosed herein may beimplemented in localized and distributed forms consistent with computingtechnology.

It should be noted that some of the system features described in thisspecification have been presented as modules, in order to moreparticularly emphasize their implementation independence. For example, amodule may be implemented as a hardware circuit comprising custom verylarge-scale integration (VLSI) circuits or gate arrays, off-the-shelfsemiconductors such as logic chips, transistors, or other discretecomponents. A module may also be implemented in programmable hardwaredevices such as field programmable gate arrays, programmable arraylogic, programmable logic devices, graphics processing units, or thelike.

A module may also be at least partially implemented in software forexecution by various types of processors. An identified unit ofexecutable code may, for instance, comprise one or more physical orlogical blocks of computer instructions that may, for instance, beorganized as an object, procedure, or function. Nevertheless, theexecutables of an identified module need not be physically locatedtogether but may comprise disparate instructions stored in differentlocations which, when joined logically together, comprise the module andachieve the stated purpose for the module. Further, modules may bestored on a computer-readable medium, which may be, for instance, a harddisk drive, flash device, random access memory (RAM), tape, or any othersuch medium used to store data.

Indeed, a module of executable code could be a single instruction, ormany instructions, and may even be distributed over several differentcode segments, among different programs, and across several memorydevices. Similarly, operational data may be identified and illustratedherein within modules and may be embodied in any suitable form andorganized within any suitable type of data structure. The operationaldata may be collected as a single data set or may be distributed overdifferent locations including over different storage devices, and mayexist, at least partially, merely as electronic signals on a system ornetwork.

It will be readily understood that the components of the application, asgenerally described and illustrated in the figures herein, may bearranged and designed in a wide variety of different configurations.Thus, the detailed description of the embodiments is not intended tolimit the scope of the application as claimed but is merelyrepresentative of selected embodiments of the application.

One having ordinary skill in the art will readily understand that theabove may be practiced with steps in a different order, and/or withhardware elements in configurations that are different than those whichare disclosed. Therefore, although the application has been describedbased upon these preferred embodiments, it would be apparent to those ofskill in the art that certain modifications, variations, and alternativeconstructions would be apparent.

While preferred embodiments of the present application have beendescribed, it is to be understood that the embodiments described areillustrative only and the scope of the application is to be definedsolely by the appended claims when considered with a full range ofequivalents and modifications (e.g., protocols, hardware devices,software platforms etc.) thereto.

What is claimed is:
 1. A system, comprising: a processor of a modelingnode; a memory on which are stored machine readable instructions thatwhen executed by the processor, cause the processor to: detect a fork ina supply-chain; resolve a branch prediction to determine a likely accesscontrol; generate a range of information based on a branch confidencelevel; and responsive to the resolution of the branch prediction, revokeaccess from a document or grant a greater access to the document basedon the range.
 2. The system of claim 1, wherein the instructions furthercause the processor to grant low-risk data based on a low confidence. 3.The system of claim 1, wherein the instructions further cause theprocessor to grant high-risk data based on a high confidence.
 4. Thesystem of claim 1, wherein the instructions further cause the processorto determine the range of information based on the supply-chain andparticipating nodes that represent organizations.
 5. The system of claim4, wherein the instructions further cause the processor to process aninput from the organizations to determine one or more types of data inthe range of information.
 6. The system of claim 1, wherein theinstructions further cause the processor to, in response to an incorrectbranch prediction, revoke a document.
 7. The system of claim 1, whereinthe instructions further cause the processor to, in response to acorrect branch prediction, reveal a full document.
 8. A method,comprising: detecting a fork in a supply-chain by a modeling node;resolving, by the modeling node, a branch prediction to determine alikely access control; generating, by the modeling node, a range ofinformation based on a branch confidence level; and responsive to theresolution of the branch prediction, revoking access from a document orgranting a greater access to the document based on the range.
 9. Themethod of claim 8, further comprising granting low-risk data based on alow confidence.
 10. The method of claim 8, further comprising grantinghigh-risk data based on a high confidence.
 11. The method of claim 8,further comprising determining the range based on the supply-chain andparticipating nodes representing organizations.
 12. The method of claim11, further comprising processing an input from the organizations todetermine one or more types of data in the range of information.
 13. Themethod of claim 8, further comprising, in response to an incorrectbranch prediction, revoking a document.
 14. The method of claim 13,further comprising, in response to a correct branch prediction,revealing a full document.
 15. A non-transitory computer readable mediumcomprising instructions, that when read by a processor, cause theprocessor to perform: detecting a fork in a supply-chain; resolving abranch prediction to determine a likely access control; generating arange of information based on a branch confidence level; and responsiveto the resolution of the branch prediction, revoking access from adocument or granting a greater access to the document based on therange.
 16. The non-transitory computer readable medium of claim 15,further comprising instructions, that when read by the processor, causethe processor to grant low-risk data based on a low confidence.
 17. Thenon-transitory computer readable medium of claim 15, further comprisinginstructions, that when read by the processor, cause the processor togrant high-risk data based on a high confidence.
 18. The non-transitorycomputer readable medium of claim 15, further comprising instructions,that when read by the processor, cause the processor to determine therange based on the supply-chain and participating nodes representingorganizations.
 19. The non-transitory computer readable medium of claim16, further comprising instructions, that when read by the processor,cause the processor to process an input from the organizations todetermine the range of one or more types of data in the range ofinformation.
 20. The non-transitory computer readable medium of claim15, further comprising instructions, that when read by the processor,cause the processor to, in response to an incorrect branch prediction,revoke a document.